Security and compliance auditing is expensive, time-consuming, and error-prone for cloud service providers operating in multiple domains. Existing approaches predominantly use formal logic and domain-specific languages to facilitate collection and validation of evidence needed for compliance certification. Such approaches do not sufficiently account for the uncertainties and challenges caused by human involvement, which are a major contributor to inefficiencies and mistakes in the audit process. We propose that hybrid approaches, in which formal, model-based approaches are combined with machine learning techniques to reason about evidence and historical audit data, are necessary to address such uncertainties. Such approaches can help both auditors and service providers better deal with uncertainties, and reduce costs, errors, and the manual effort required to identify evidence needed for compliance certification. We present a taxonomic framework for understanding the causes of and potential solutions to uncertainty in the audit process. We identify areas within evidence collection and validation in which machine learning can augment model-based techniques to reduce uncertainties. We provide some examples of hybrid approaches that we are exploring and discuss the need for more work in this area.

Concert, a high-level-language approach to programming heterogeneous distributed systems, is described. The Concert model introduces a small set of language extensions into conventional procedural languages. These language extensions support a cooperative peer process model which addresses in the distributed environment the same issues addressed by language semantics in the conventional environment. The Concert implementation provides layered support for these language extensions, bridging a different source of heterogeneity at each layer. A prototype Concert system currently includes C programs running on OS/2 on multiple PS/2s communicating via calls with one another as well as with PL/I programs running on VM/370.>

A direct structure access approach called token relabeling scheme is presented in which all array operations can be performed without the use of any intermediary structure memory. The graph constructs for both approaches are described. Four numerical algorithms including fast Fourier transform, bitonic sort, LU decomposition, and matrix multiplication are implemented in both approaches. Token relabeling is directly applicable to arrays which are entirely consumed. Graph constructs which allow partial consumption are also designed. The effectiveness and efficiency of this parallel random access construct verifies the feasibility and applicability of the token relabeling scheme. A deterministic simulation of Arvind and K.P. Gostelow's tagged-token data-flow architecture (1982) is undertaken to validate the graph designs and evaluate the performance of the graphs. It is shown that the direct access graphs present better performance with regard to execution time, speedup, and resource utilization.>

Presents a demand-driven evaluation system for list-structure language systems, using the functional language FP. It enables execution in a data-driven environment. A formal approach for transforming FP programs into lazy programs, which contain the notion of demands, is used. The superset language of FP is called DFP (demand-driven FP). A demand reduction scheme is used to remove unnecessary demand propagations on DFP programs to reduce run-time overhead. The DFP programs are translated into data-flow graphs according to the graph schemata developed from the FP-DFP transformation rules. The execution characteristics of the DFP graphs are identified and the architecture supports for efficient execution are suggested. The system allows programming in FP by infinite data structures and the application of partial-function-value evaluation. Examples of these applications are used to demonstrate the transformation process, the principles of run-time interpretation, the effectiveness of the transformation, and the power of the evaluation system.>